};

struct TFE_MonitoringBoolGauge0 : TFE_MonitoringGauge<bool, 0> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringBoolGauge1 : TFE_MonitoringGauge<bool, 1> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringBoolGauge2 : TFE_MonitoringGauge<bool, 2> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};

struct TFE_MonitoringBuckets {

  // `keep_alive_secs` of inactivity.
  virtual Status SetOrUpdateServerDef(const ServerDef& server_def,
                                      bool reset_context, int keep_alive_secs,
                                      int64_t init_timeout_in_ms, int retries,
                                      bool clear_existing_contexts = false) = 0;

  // Initializes context for the local worker and no contexts will be created

#include "tensorflow/core/platform/test.h"

namespace {

void TestRemoteExecuteSilentCopiesFunc(bool async, bool remote,
                                       bool heavy_load_on_streaming_rpc,
                                       bool remote_func_outputs = false,
                                       bool has_packed_input = false) {
  return TestRemoteExecuteSilentCopies(async, remote, /*func=*/true,

  outputs[0] = temp_outputs[1];
  temp_outputs[0]->Unref();
  return absl::OkStatus();
}

class CppGradients
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    status_ = StatusFromTF_Status(status.get());

  // Hint: use c.release()() to run early.
  F release() {
    released_ = true;
    return std::move(f_);
  }

  bool is_released() const { return released_; }

 private:
  static_assert(!std::is_reference<F>::value, "F must not be a reference");

  bool released_ = false;
  F f_;
};

template <int&... ExplicitParameterBarrier, typename F,
          typename DecayF = typename std::decay<F>::type>

#include "tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Register the POSIX filesystems statically.
// Return value will be unused
bool StaticallyRegisterLocalFilesystems() {
  TF_FilesystemPluginInfo info;
  TF_InitPlugin(&info);
  Status status = filesystem_registration::RegisterFilesystemPluginImpl(&info);
  if (!status.ok()) {

  // with key `key` existed after the call.
  bool Delete(const std::string& key) {
    absl::MutexLock lock(&mu_);
    return DeleteLocked(key);
  }

  /// Look up the entry with key `key` and copy it to `value` if found. Returns
  /// true if an entry was found for `key`, and its timestamp is not more than
  /// max_age_ seconds in the past.
  bool Lookup(const std::string& key, T* value) {
    if (max_age_ == 0) {

                     const char* name = "split3");

bool IsPlaceholder(const tensorflow::NodeDef& node_def);

bool IsScalarConst(const tensorflow::NodeDef& node_def, int v);

bool IsAddN(const tensorflow::NodeDef& node_def, int n);

bool IsNeg(const tensorflow::NodeDef& node_def, const string& input);

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def);

TempFile::~TempFile() {
  std::fstream::close();
  std::remove(name_.c_str());
}

const std::string TempFile::getName() const { return name_; }

bool TempFile::truncate() {
  std::fstream::close();
  std::fstream::open(name_, std::ios::binary | std::ios::out);
  return std::fstream::is_open();

namespace tensorflow {
namespace gradients {
namespace internal {

void CompareNumericalAndAutodiffGradients(
    Model model, Model grad_model, AbstractContext* ctx,
    absl::Span<AbstractTensorHandle* const> inputs, bool use_function,
    double abs_error = 1e-2);

void CheckTensorValue(AbstractTensorHandle* t, absl::Span<const float> manuals,
                      absl::Span<const int64_t> dims, double abs_error = 1e-2);